scholarly journals Comparison of Least Significant Bit, Pixel Value Differencing, and Modulus Function on Steganography to Measure Image Quality, Storage Capacity, and Robustness

2021 ◽  
Vol 1751 ◽  
pp. 012039
Author(s):  
D Darwis ◽  
N B Pamungkas ◽  
Wamiliana
Keyword(s):  
Image Quality ◽  
Storage Capacity ◽  
Modulus Function ◽  
Least Significant Bit ◽  
Pixel Value ◽  
Pixel Value Differencing

Steganography Techniques Based on Modulus Function and PVD Against PDH Analysis and FOBP

2019 ◽  
pp. 157-184
Keyword(s):  
Signal To Noise Ratio ◽  
Experimental Results ◽  
Modulus Function ◽  
Evaluation Function ◽  
Embedding Capacity ◽  
Least Significant Bit ◽  
Rs Analysis ◽  
Block Data ◽  
Pixel Value ◽  
Pixel Value Differencing

This chapter proposes two improved steganography techniques by addressing two problems in the existing literature. The first proposed technique is modulus function-based steganography and it addresses pixel difference histogram (PDH) analysis. The modulus function is used to calculate an evaluation function and based on the value of the evaluation function embedding decision is taken. There are two variants of this technique: (1) modulus 9 steganography and (2) modulus 16 steganography. In modulus 9 steganography, the embedding capacity in a pair of pixels is 3 bits, and in modulus 16 steganography the embedding capacity in a pair of pixels is 4 bits. Both the variants possess higher PSNR values. The experimental results prove that the PDH analysis cannot detect this technique. The second proposed technique is based on pixel value differencing with modified least significant bit (MLSB) substitution and it addresses fall off boundary problem (FOBP). This technique operates on 2×2 pixel blocks. In one of the pixels of a block data hiding is performed using MLSB substitution. Based on the new value of this pixel, three difference values with three neighboring pixels are calculated. Using these difference values, PVD approach is applied. Experimental results prove that the PDH analysis and RS analysis is unable to detect this proposed technique. The recorded values of bit rate and peak signal-to-noise ratio are also satisfactory.

scholarly journals High Capacity Image Steganography Using Modified LSB Substitution and PVD against Pixel Difference Histogram Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Gandharba Swain
Keyword(s):  
Boundary Problem ◽  
High Capacity ◽  
Experimental Results ◽  
Least Significant Bit ◽  
Rs Analysis ◽  
Distortion Measure ◽  
Pixel Value ◽  
Pixel Value Differencing ◽  
Difference Histogram ◽  
Lsb Substitution

The combination of pixel value differencing (PVD) and least significant bit (LSB) substitution gives higher capacity and lesser distortion. However, there are three issues to be taken into account: (i) fall off boundary problem (FOBP), (ii) pixel difference histogram (PDH) analysis, and (iii) RS analysis. This paper proposes a steganography technique in two variants using combination of modified LSB substitution and PVD by taking care of these three issues. The first variant operates on 2 × 3 pixel blocks and the second technique operates on 3 × 3 pixel blocks. In one of the pixels of a block, embedding is performed using modified LSB substitution. Based on the new value of this pixel, difference values with other neighboring pixels are calculated. Using these differences, PVD approach is applied. The edges in multiple directions are exploited, so PDH analysis cannot detect this steganography. The LSB substitution is performed in only one pixel of the block, so RS analysis also cannot detect this steganography. To address the FOBP, suitable equations are used during embedding procedure. The experimental results such as bit rate and distortion measure are satisfactory.

Statistical Feature–Based Steganalysis for Pixel-Value Differencing Steganography

2021 ◽  
Author(s):  
Wen-Bin Lin ◽  
Tai-Hung Lai ◽  
Ko-Chin Chang
Keyword(s):  
Least Significant Bit ◽  
Stego Image ◽  
Image Steganalysis ◽  
Detection Analysis ◽  
Suitable Parameter ◽  
Feature Based ◽  
Pixel Value ◽  
Pixel Value Differencing ◽  
Difference Histogram ◽  
Advance Knowledge

Abstract The security and embedding capacity of pixel-value differencing (PVD) steganography is superior to that of least significant bit replacement steganography. Several studies have proposed extended PVD steganography methods that use the original concept of PVD steganography. The majority of the studies have verified their security against regular-singular detection analysis or pixel difference histogram attacks. Weighted stego image steganalysis is the state-of-the-art technology for PVD steganography. This study proposed a suitable parameter for the estimator based on different relative embedding ratios and the size of normal embedding blocks. The experimental results revealed that the proposed technology does not require advance knowledge of the original image. In addition, the proposed method is accurate and precise at any embedding ratio. In the future, this method may be utilized to analyze the security of extended PVD steganography.

A Review on LSB Substitution and PVD Based Image Steganography Techniques

2016 ◽  
Vol 2 (3) ◽  
pp. 712 ◽  
Author(s):  
Aditya Kumar Sahu ◽  
Gandharba Swain
Keyword(s):  
Information And Communication Technologies ◽  
Data Communication ◽  
Communication Technologies ◽  
Least Significant Bit ◽  
Hiding Capacity ◽  
Information And Communication ◽  
Distortion Measure ◽  
Pixel Value ◽  
Pixel Value Differencing ◽  
Lsb Substitution

<p>There has been a tremendous growth in Information and Communication technologies during the last decade. Internet has become the dominant media for data communication. But the secrecy of the data is to be taken care. Steganography is a technique for achieving secrecy for the data communicated in Internet. This paper presents a review of the steganography techniques based on least significant bit (LSB) substitution and pixel value differencing (PVD). The various techniques proposed in the literature are discussed and possible comparison is done along with their respective merits. The comparison parameters considered are, (i) hiding capacity, (ii) distortion measure, (iii) security, and (iv) computational complexity.</p>

scholarly journals PERBANDINGAN ALGORITMA PIXEL VALUE DIFFERENCING DAN MODULUS FUNCTION PADA STEGANOGRAFI UNTUK MENGUKUR KUALITAS CITRA DAN KAPASITAS PENYIMPANAN

2020 ◽  
Vol 20 (1) ◽  
pp. 67-77
Author(s):  
Nurhuda Budi Pamungkas ◽  
Dedi Darwis ◽  
Ditha Nurjayanti ◽  
Agung Tri Prastowo
Keyword(s):  
Modulus Function ◽  
Pixel Value ◽  
Pixel Value Differencing

scholarly journals Information Trouncing Via Slightest Momentous Spot System Procedure

2018 ◽  
Vol 7 (3.27) ◽  
pp. 488
Author(s):  
D Saravanan ◽  
N Sivaprasad ◽  
Dennis Joseph
Keyword(s):  
Visual Quality ◽  
Secret Message ◽  
Pseudorandom Number Generator ◽  
Least Significant Bit ◽  
Pixel Value ◽  
The Difference ◽  
Pixel Value Differencing ◽  
The Relationship ◽  
Embedding Rate

The least-significant-bit based approach is a popular type of stenographic algorithms in the spatial domain. However, we find that in most existing approaches, the choice of embedding positions within a cover audio mainly depends on a pseudorandom number generator without considering the relationship between the audio content itself and the size of the secret message. In this paper, we expand the least significant bit matching revisited audio stegnography and propose an edge adaptive scheme which can select the embedding regions according to the size of secret message and the difference between two consecutive pixels in the cover audio. For lower embedding rates, only sharper edge regions are used while keeping the other smoother regions as they are. When the embedding rate increases, more edge regions can be released adaptively for data hiding by adjusting just a few parameters. New scheme can enhance the security significantly compared with typical least significant bit-based approaches as well as their edge adaptive ones, such as pixel-value-differencing-based approaches, while preserving higher visual quality of stegno audios at the same time.  

scholarly journals Digital Image Steganography Using Eight-Directional PVD against RS Analysis and PDH Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Gandharba Swain
Keyword(s):  
Least Significant Bit ◽  
Hiding Capacity ◽  
Central Pixel ◽  
Rs Analysis ◽  
Pixel Value ◽  
Pixel Value Differencing ◽  
Difference Histogram ◽  
Lsb Substitution

The least significant bit (LSB) substitution techniques are detected by RS analysis and the traditional pixel value differencing (PVD) approaches are detected by pixel difference histogram (PDH) analysis. The PVD steganography can escape from PDH analysis by using the edges in multiple directions. This paper proposes a steganography technique by exploiting the edges in eight directions and also using LSB substitution to resist from both RS analysis and PDH analysis. For every 3×3 pixel block the central pixel is embedded with 3 or 4 bits of data by modified LSB substitution technique. Then this new value of the central pixel is utilized to calculate eight difference values with eight neighboring pixels. These eight difference values are used to hide the data. There are two types with regard to two different range tables. Type 1 uses 3 bit modified LSB substitution and range table 1. Type 2 uses 4 bit modified LSB substitution and range table 2. Type 1 and type 2 are also known as variant 1 and variant 2, respectively. Type 1 possesses higher PSNR and type 2 possesses higher hiding capacity.

scholarly journals A Comparative Analysis of LSB, MSB and PVD Based Image Steganography

2021 ◽  
Vol 8 (9) ◽  
pp. 373-377
Author(s):  
Alade Oluwaseun. Modupe ◽  
Amusan Elizabeth Adedoyin ◽  
Adedeji Oluyinka Titilayo
Keyword(s):  
Comparative Analysis ◽  
Performance Metrics ◽  
Similarity Index ◽  
Image Steganography ◽  
Secret Message ◽  
Future Research ◽  
Least Significant Bit ◽  
Comparative Performance ◽  
Pixel Value ◽  
Pixel Value Differencing

Steganography is the art and science of hiding information by embedding data into cover media. Numerous techniques are designed to provide the security for the communication of data over the Internet. A good steganographic algorithm is recognized by the performance of the techniques measured with the support of the performance metrics among which are PSNR, MSE, SSIM, robustness and capacity to hide the information in the cover image. In this paper a comparative analysis of Least Significant Bit (LSB), Most Significant Bit (MSB) and Pixel Value Differencing (PVD) image steganography in grayscale and colored images was performed. Three different cover images was used to hide secret message. A comparative performance analysis of LSB, MSB and PVD methods used in image steganography was performed using peak signal to noise ratio (PSNR), Mean square error (MSE) and Structural Similarity index (SSIM) as performance metrics. LSB technique gives higher PSNR and SSIM values than MSB and PVD method with lower MSE than the other two techniques. Future research can be geared towards investigating the embedding capacity, security, and computational complexity of each technique. Keywords: Least Significant Bit (LSB), Most Significant Bit (MSB), Pixel value differencing (PVD), PSNR, SSIM and MSE,

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